Machines use Google-type algorithms on biopsy images to help children get treatment faster. A study published in the open access journal JAMA Open Network today by scientists at the University of Virginia schools of Engineering and Medicine says machine learning algorithms applied to biopsy images can shorten the time for diagnosing and treating a gut disease that often causes permanent physical and cognitive damage in children from impoverished areas. In places where sanitation, potable water and food are scarce, there are high rates of children suffering from environmental enteric dysfunction, a disease that limits the gut's ability to absorb essential nutrients and can lead to stunted growth, impaired brain development and even death. The disease affects 20 percent of children under the age of 5 in low- and middle-income countries, such as Bangladesh, Zambia and Pakistan, but it also affects some children in rural Virginia. For Dr. Sana Syed, an assistant professor of pediatrics in the UVA School of Medicine, this project is an example of why she got into medicine.
Driven by the rise of transformative digital technologies and the proliferation of data, human storytelling is rapidly evolving in ways that challenge and expand our very understanding of narrative. Transmedia -- where stories and data operate across multiple platforms and social transformations -- and its wide range of theoretical, philosophical, and creative perspectives, needs shared critique around making and understanding. MIT's School of Architecture and Planning (SA P), working closely with faculty in the MIT School of Humanities, Arts, and Social Sciences (SHASS) and others across the Institute, has launched the Transmedia Storytelling Initiative under the direction of Professor Caroline Jones, an art historian, critic, and curator in the History, Theory, Criticism section of SA P's Department of Architecture. The initiative will build on MIT's bold tradition of art education, research, production, and innovation in media-based storytelling, from film through augmented reality. Supported by a foundational gift from David and Nina Fialkow, this initiative will create an influential hub for pedagogy and research in time-based media.
This UC Berkeley School of Information online short course is delivered in collaboration with GetSmarter. Learn from industry thought leaders as you gain the skills needed to develop an AI strategy, and lead the transformation in your organization. The design of this online course is guided by UC Berkeley School of Information faculty and industry experts who will share their experience and in-depth subject knowledge with you throughout the course.
I am often asked about artificial intelligence and the future of work. My answer is that A.I. will change 100% of current jobs. It will change the job of a software developer, of a customer service agent, of a professional driver. And it will change my job as the CEO of one of the biggest technology companies in the world. Yet notice my choice of words: A.I. will change jobs but it won't replace all of them.
An interdisciplinary center that integrates artificial intelligence, data science and genomic screening--the first of its kind in New York City--is slated to open in late 2021. Mount Sinai's Icahn School of Medicine announced on Tuesday the launch of the Hamilton and Amabel James Center for Artificial Intelligence and Human Health, which will be staffed by about 40 principal investigators and 250 graduate students, postdoctoral fellows and computer scientists. "Mount Sinai has consistently been at the forefront of advancing healthcare across medical disciplines and this initiative represents our next step forward in building on that legacy," says Kenneth Davis, MD, Mount Sinai Health System's president and CEO. "We see the potential of artificial intelligence to radically transform the care that patients receive, and we want to shape and lead this effort. Davis added that the new center will serve as a "hub where our talented researchers can collaborate in unprecedented ways and bring forward ideas and innovative technologies that achieve better outcomes for our patients."
Doctors could soon get some help from an artificial intelligence tool when diagnosing brain aneurysms -- bulges in blood vessels in the brain that can leak or burst open, potentially leading to stroke, brain damage or death. The AI tool, developed by researchers at Stanford and detailed in a paper published June 7 in JAMA Network Open, highlights areas of a brain scan that are likely to contain an aneurysm. "There's been a lot of concern about how machine learning will actually work within the medical field," said Allison Park, a graduate student in statistics and co-lead author of the paper. "This research is an example of how humans stay involved in the diagnostic process, aided by an artificial intelligence tool." This tool, which is built around an algorithm called HeadXNet, improved clinicians' ability to correctly identify aneurysms at a level equivalent to finding six more aneurysms in 100 scans that contain aneurysms.
I mentioned in my last article that Artificial Intelligence is a large field, to get to being a large field it must have been around for some time, which it has. The term Artificial Intelligence (AI) was coined in 1956 at the Dartmouth Conference (New Hampshire) by Stanford University Professor John McCarthy (although he was an assistant professor at Dartmouth at the time). You could argue that AI has deep roots in Formal Reasoning but that would open up a huge philosophical debate and would probably take significantly more space and time to write and read! So why now, if AI has been around for 70 years what has changed in the past few years that has propelled AI into the mainstream? The answer is that the perfect wave has hit, three things have come together to give us the adoption rates that we see.
A brain aneurysm is a bulge that forms in the blood vessel of your brain that could lead to severe health issues and possibly death. The diagnosis of this aneurysms is a critically important clinical task. Now, a team of researchers at Stanford University has developed an artificial intelligence (AI) tool that can help detect brain aneurysms. The tool highlights areas of a brain scan that are likely to contain an aneurysm. "There's been a lot of concern about how machine learning will actually work within the medical field," said Allison Park, a Stanford graduate student in statistics and co-lead author of the paper.
MONTREAL, June 4, 2019 /CNW Telbec/ - Today's students are graduating into a world that is in a significant state of transformation due to developments in Artificial Intelligence (AI) and related information technologies. "Our current and future students are the ones who will be facing these challenges and opportunities when they enter university or the work force. We are committed to offering new, updated and upgraded classes and learning opportunities to help prepare our students adequately," said Richard Filion, Director General of Dawson College. As a sign of that commitment to its students, Dawson College has decided to make an investment of over a million dollars in a comprehensive Artificial Intelligence initiative, the largest investment in an AI project by a cégep in Quebec. Today the College announced that a three-year strategic plan for the academic years 2019-2022 has been adopted and that $1,050,000 has been budgeted for its implementation, hoping to establish Dawson College as the centre of excellence in AI in college education.
Last year Kate Crawford, a New York University professor who runs an artificial intelligence research centre, set out to study the "black box" of processes that exist around the hugely popular Amazon Echo device. Crawford did not do what you might expect when approaching AI – namely, study algorithms, computing systems and suchlike. Instead, she teamed up with Vladan Joler, a Serbian academic, to map the supply chains, raw materials, data and labour that underpin Alexa, the AI agent that Echo's users talk to. It was a daunting process – so much so that Joler and Crawford admit that their map, Anatomy of an AI System, is just a first step. The results are both chilling and challenging.